Abstract: An image capture application captures a sequence of images via a digital camera. The sequence of images may have undesirable levels of blurriness due to the motion of objects in the field of view of the digital camera or due to movement of the digital camera itself. A deblur engine within the image capture application generates image segments within one of the captured images, where a given image segment includes pixel values that move coherently between different images in the sequence. The deblur engine then deblurs each image segment based on the coherent motion of each different image segment and combines the resultant, deblurred image segments into a deblurred image. Advantageously, blurriness caused by the combined effects of moving objects and camera motion may be reduced, thereby improving the ability of a digital camera to provide high-quality images. As such, the user experience of digital photography may be enhanced.

Abstract: The amount of power and processing needed to enable more previze gesture input for a computing device can be reduced by utilizing one or more gesture sensors along with a conventional camera. Information associated with an image, such as color information, acquired from the conventional camera can be mapped to one or more gesture sensors (e.g., low resolution, greyscale or monochrome camera sensors) of a computing device. The mapped information between the conventional camera and the gesture sensors can be used for purposes such as gesture- and/or motion-based approaches.

Abstract: An image processing apparatus generates, from the captured image, a plurality of images, which respectively corresponds to ranges of individual subject distances. The apparatus then applies image processing to at least one of the images in accordance with an instruction to change the shooting distance and field angle of the captured image, and generates a combined image that corresponds to the changed shooting distance and field angle. The image processing is applied to at least one of the images such that the size of a primary image in the combined image after changing the shooting distance and the field angle does not change.

Abstract: A method of generating a three-dimensional (3D) image of a target object includes acquiring ultrasound data of the target object; and generating the 3D image of the target object by using the ultrasound data so that a part of the target object having attribute information different than attribute information of other parts of the target object is shown on the 3D image differently than the other parts.

Abstract: In order to classify the presented pose of a human hand, a feature distribution map of the pose is compared to reference feature distribution maps. To generate a feature distribution map, each contour point of a hand is analyzed to determine a corresponding feature set. The feature set of a contour point includes a distance feature and an angle feature of the contour point in relation to one of its neighboring contour points. The feature sets generated from an observed pose are compared to feature sets of reference poses to determine which of the reference poses most closely matches the presented pose.

Abstract: A computer-implemented method and system register plural images using a computer processor and computer memory, where computer code stored in the computer memory causes the computer processor to perform the registration. The registration includes receiving a reference image; receiving a sensed image; computing an approximate image transformation between the reference image and the sensed image; finding plural candidate tie points by utilizing template matching; applying radiometric filtering to at least a portion of the plural candidate tie points; applying geometric filtering to at least a portion of the plural candidate tie points; computing a calculated image transformation using candidate points of the plural candidate points that were not filtered out by the radiometric and geometric filtering; transforming the sensed image using the calculated image transformation; and registering the sensed image with the reference image.

Abstract: The present invention concerns a method of optically assessing a wind power installation or a part thereof, in particular a rotor blade, including the steps: orienting a camera on to a region to be assessed, recording a photograph of the region to be assessed with the camera, detecting the position of the photographed region, and associating the ascertained position with the photographed region.

Abstract: The provided is an image processing method, which includes: converting a to-be-processed image into a gray image; performing Gaussian blur processing having a predefined fuzzy radius on the gray image, and obtaining a reference image; and according to gray values of reference pixels of the reference image, decreasing a pixel value of a pixel of the to-be-processed image corresponding to a reference pixel whose gray value is larger than a gray threshold, increasing a pixel value of a pixel of the to-be-processed image corresponding to a reference pixel whose gray value is smaller than the gray threshold, and obtaining an adjusted image.

Abstract: A method and a system for obtaining a high-resolution image of a volume of a sample using laser imaging are provided. The method includes a step of probing the volume of the sample with a first excitation beam having an intensity profile of maximum intensity at a center thereof, thereby obtaining a positive image of the volume. The method also includes a step of probing the volume of the sample with a second excitation beam having an intensity profile of minimum intensity at a center thereof and defining a peripheral region of maximum intensity around the center, thereby obtaining a negative image of the volume. The method finally includes a step of subtracting the negative image from the positive image, thereby obtaining the high-resolution image of the volume of the sample. Advantageously, embodiments of the invention can be probe- and fluorescence-independent, and be conveniently retrofitted into existing laser imaging systems.

Abstract: Various embodiments provide a method for computing color descriptors of product images. For example, a number of fine color representatives can be determined to describe color variation in an image as a histogram by assigning a saturation value and a brightness value to a plurality of color hues. For each pixel of the image, the closest color among a defined fine color representative set is computed. In this example, each of the pixels is assigned a color ID corresponding to their closest matching fine color representative and at least one family color ID corresponding one or more pure color families. In this example, a histogram of the color representatives and a histogram for the color families are computed. A single color vector descriptor for the image is then determined by combining the family histogram with the color representative histogram.

Abstract: Image classification and related imaging tasks performed using machine learning tools may be accelerated by using one or more of such tools to associate an image with a cluster of such labels or categories, and then to select one of the labels or categories of the cluster as associated with the image. The clusters of labels or categories may comprise labels that are mutually confused for one another, e.g., two or more labels or categories that have been identified as associated with a single image. By defining clusters of labels or categories, and configuring a machine learning tool to associate an image with one of the clusters, processes for identifying labels or categories associated with images may be accelerated because computations associated with labels or categories not included in the cluster may be omitted.

Abstract: Identifying whether an image includes a search image can be accomplished using region analysis and/or parts model analysis. Region analysis can include dividing a received image into regions and analyzing each region by: enlarging the region, applying a gradient histogram transformation to the enlarged region, and comparing the transformed region, at various angles, to a set of search patterns. Parts model analysis can include identifying key features of an image such as prominent lines or areas, objects or object edges, consecutive colors; generating one or more parts models from the key features by representing the key features as geometric objects; and comparing each parts model, at various angles, to a set of search patterns. The comparison employed in region analysis or parts model analysis can employ classifiers trained on the search images.

Abstract: Disclosed is an image feature extraction method including a step of defining a combination of at least two kinds of solid angles along at least two directions, of an input spherical image; a step of determining respective values of the combination of the at least two kinds of solid angles, so that surface areas of spherical crowns of spherical segments, which are obtained by dividing the spherical image by the respective values of the combination of the at least two kinds solid angles, have a same value; and a step of generating, by utilizing the respective values of the combination of the at least two kinds of solid angles, an image feature template so as to conduct image feature extraction.

Abstract: Methods and systems for recalibrating sensing devices without using familiar targets are provided herein. The method may include: capturing a scene using a sensing device; determining whether or not the device is calibrated; in a case that said sensing device is calibrated, adding at least one new landmark to the known landmarks; in a case that said sensing device is not calibrated, determining at least some of the captured objects as objects stored on a database as known landmarks at the scene whose position is known; and calibrating the sensing device based on the known landmarks. The system may have various architectures that include a sensing device which captures images of the scene and further derive 3D data on the scene of some form.

Abstract: A computer-implemented method of performing fingerprint based authentication from matching local features represented by binary features which can be matched in an efficient implementation in one or both of software and hardware by computing Hamming distances between the binary features. A local feature in a verification image is said to be matching with a local feature in an enrolment image if the Hamming distance between the binary features falls below a pre-determined threshold. The computer-implemented method retains information about the similarity of local features in the two images and utilities it in an efficient way with the objective of improving fingerprint recognition rates and enabling finger liveness detection. In an aspect a normalized feature similarity distribution is generated as part of the representation in recognition and liveness detection.

Abstract: An image processing display and an image processing display program that can prevent interference with catheter treatment even when the distal end of a catheter is located behind a treatment apparatus on X-ray fluoroscopic images. The image processing display displays X-ray fluoroscopic images to be obtained by looking through a region including blood vessels using X-rays during treatment, and includes a treatment apparatus image extractor and an image processor. The treatment apparatus image extractor, based on X-ray fluoroscopic images, extracts treatment apparatus images representing the treatment apparatus having the property of absorbing X-rays. The image processor determines the distal end position of the catheter to superimpose and display images representing the determined distal end position of the catheter on the region of the X-ray fluoroscopic images showing the treatment apparatus.

Abstract: When a positional relationship between reference blocks differs from a positional relationship between comparison blocks, a filtering device replaces the corresponding comparison blocks to update positional relationship information (order of correlations and the positional relationship thereof) into a state where the information should be and, thus, appropriately derives a difference value of an object so that the positional relationship between the reference blocks become identical to the positional relationship between the comparison blocks.

Abstract: Methods, apparatuses, and embodiments related to analyzing the content of digital images. A computer extracts multiple sets of visual features, which can be keypoints, based on an image of a selected object. Each of the multiple sets of visual features is extracted by a different visual feature extractor. The computer further extracts a visual word count vector based on the image of the selected object. An image query is executed based on the extracted visual features and the extracted visual word count vector to identify one or more candidate template objects of which the selected object may be an instance. When multiple candidate template objects are identified, a matching algorithm compares the selected object with the candidate template objects to determine a particular candidate template of which the selected object is an instance.

Abstract: A method of authenticating a candidate fingerprint by means of an electronic device comprising a touch sensor; and a fingerprint sensor. The method comprises the steps of: acquiring at least one touch sensor signal indicative of a sub-area of the touch sensor being touched by the candidate finger; acquiring at least one fingerprint image of the candidate fingerprint; retrieving a stored enrollment representation of the enrolled fingerprint of the enrolled finger; determining an authentication representation of the candidate fingerprint based on the fingerprint image; and determining an authentication result based on the authentication representation, the stored enrollment representation, and the at least one touch sensor signal.

Abstract: A pair of images is obtained having pixel intensities substantially proportional to wave height for a majority of pixels. The images are aligned, orthorectified, and adjusted for relative reflectance in their respective spectral bands. The images are Fourier transformed, and then one image is propagated to the time of the other image. A deglinted image is calculated by taking the difference in wavenumber space, then inverse Fourier transforming. Alternatively, an equivalent formula can be obtained using convolutions. The propagation uses a gravity wave propagation function, which, in general, can be a function of depth, surface current, and wave direction which can be obtained from external data, assumed constant, or calculated from wave images depending on the particular circumstances.